Olivier David

Bacterial protein signals are associated with Crohn’s disease

Objective No Crohn’s disease (CD) molecular maker has advanced to clinical use, and independent lines of evidence support a central role of the gut microbial community in CD. Here we explore the feasibility of extracting bacterial protein signals relevant to CD, by interrogating myriads of intestinal bacterial proteomes from a small number of patients and healthy controls. Design We first developed and validated a workflow—including extraction of microbial communities, two-dimensional difference gel electrophoresis (2D-DIGE), and LC-MS/MS—to discover protein signals from CD-associated gut microbial communities. Then we used selected reaction monitoring (SRM) to confirm a set of candidates. In parallel, we used 16S rRNA gene sequencing for an integrated analysis of gut ecosystem structure and functions. Results Our 2D-DIGE-based discovery approach revealed an imbalance of intestinal bacterial functions in CD. Many proteins, largely derived from Bacteroides species, were over-represented, while under-represented proteins were mostly from Firmicutes and some Prevotella members. Most overabundant proteins could be confirmed using SRM. They correspond to functions allowing opportunistic pathogens to colonise the mucus layers, breach the host barriers and invade the mucosae, which could still be aggravated by decreased host-derived pancreatic zymogen granule membrane protein GP2 in CD patients. Moreover, although the abundance of most protein groups reflected that of related bacterial populations, we found a specific independent regulation of bacteria-derived cell envelope proteins. Conclusions This study provides the first evidence that quantifiable bacterial protein signals are associated with CD, which can have a profound impact on future molecular diagnosis.

DESIGNS FOR INTERFERENCE

Treatments are often assessed in small experimental units to economize on resources. Treatment differences for the large units used in practice may then be poorly estimated because of interference. Using prior information on treatments, designs are proposed which control interference by ensuring that treatments in neighboring units are similar. Interference may then be ignored in the analysis. Two types of designs are considered: block designs which are based on the concurrence of treatments in the same block, and neighbor designs which take account of the concurrence of treatments in adjacent units.

Dynamics of adaptation in spatially heterogeneous metapopulations.

The selection pressure experienced by organisms often varies across the species range. It is hence crucial to characterise the link between environmental spatial heterogeneity and the adaptive dynamics of species or populations. We address this issue by studying the phenotypic evolution of a spatial metapopulation using an adaptive dynamics approach. The singular strategy is found to be the mean of the optimal phenotypes in each habitat with larger weights for habitats present in large and well connected patches. The presence of spatial clusters of habitats in the metapopulation is found to facilitate specialisation and to increase both the level of adaptation and the evolutionary speed of the population when dispersal is limited. By showing that spatial structures are crucial in determining the specialisation level and the evolutionary speed of a population, our results give insight into the influence of spatial heterogeneity on the niche breadth of species.

Increasing ursodeoxycholic acid in the enterohepatic circulation of pigs through the administration of living bacteria.

We investigated the feasibility of increasing ursodeoxycholic acid (UDCA) in the enterohepatic circulation of pigs by administering living bacteria capable of epimerising endogenous amidated chenodeoxycholic acid (CDCA) to UDCA. We first demonstrated that combining Bifidobacterium animalis DN-173 010, as a bile salt-hydrolysing bacterium, and Clostridium absonum ATCC 27555, as a CDCA to UDCA epimerising bacterium, led to the efficient epimerisation of glyco- and tauro-CDCA in vitro, with respective UDCA yields of 55.8 (SE 2.8) and 36.6 (SE 1.5)%. This strain combination was then administered to hypercholesterolaemic pigs over a 3-week period, as two daily preprandial doses of either viable (six experimental pigs) or heat-inactivated bacteria (six controls). The main effects of treatment were on unconjugated bile acids (P=0.035) and UDCA (P<0.0001) absorbed into the portal vein, which increased 1.6-1.7- and 3.5-7.5-fold, respectively, under administration of living compared with inactivated bacteria. In bile, UDCA did not increase significantly, but the increase in biliary lithocholic acid with time in the controls was not observed in the experimental pigs (P=0.007), and the same trend was observed in faeces. All other variables (biliary lipid equilibrium, plasma lipid levels and partition of cholesterol between the different lipoprotein classes) remained unaffected by treatment throughout the duration of the experiment. In conclusion, it is feasible to increase the bioavailability of UDCA to the intestine and the liver by administering active bacteria. This may represent an interesting new probiotic activity, provided that in future it could be expressed by a safe food micro-organism.

Coalescent-Based DNA Barcoding: Multilocus Analysis and Robustness

DNA barcoding is the assignment of individuals to species using standardized mitochondrial sequences. Nuclear data are sometimes added to the mitochondrial data to increase power. A barcoding method for analysing mitochondrial and nuclear data is developed. It is a Bayesian method based on the coalescent model. Then this method is assessed using simulated and real data. It is found that adding nuclear data can reduce the number of ambiguous assignments. Finally, the robustness of coalescent-based barcoding to departures from model assumptions is studied using simulations. This method is found to be robust to past population size variations, to within-species population structures, and to designs that poorly sample populations within species. Supplementary Material is available online at www.liebertonline.com/cmb.

Estimation of Plant Demographic Parameters from Stage-Structured Censuses

This article presents some statistical methods for estimating the parameters of a population dynamics model for annual plants. The model takes account of reproduction, immigration, seed survival in a seed bank, and plant growth. The data consist of the number of plants in several developmental stages that were measured in a number of populations for a few consecutive years; they are incomplete since seeds could not be counted. It is assumed that there are no measurement errors or that measurement errors are binomial and not frequent. Some statistical methods are developed within the framework of estimating equations or Bayesian inference. These methods are applied to oilseed rape data.